Overview

Dataset statistics

Number of variables10
Number of observations99999
Missing cells0
Missing cells (%)0.0%
Duplicate rows0
Duplicate rows (%)0.0%
Total size in memory8.4 MiB
Average record size in memory88.0 B

Variable types

Numeric9
Categorical1

Reproduction

Analysis started2024-10-04 03:15:25.329879
Analysis finished2024-10-04 03:15:46.280613
Duration20.95 seconds
Software versionydata-profiling v4.8.3
Download configurationconfig.json

Variables

alpha
Real number (ℝ)

Distinct99998
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean177.62865
Minimum0.0055278279
Maximum359.99981
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 MiB
2024-10-04T10:15:46.547379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum0.0055278279
5-th percentile11.750782
Q1127.5177
median180.90053
Q3233.89501
95-th percentile348.76986
Maximum359.99981
Range359.99428
Interquartile range (IQR)106.37731

Descriptive statistics

Standard deviation96.502612
Coefficient of variation (CV)0.54328291
Kurtosis-0.53720514
Mean177.62865
Median Absolute Deviation (MAD)53.202785
Skewness-0.028497514
Sum17762688
Variance9312.7541
MonotonicityNot monotonic
2024-10-04T10:15:46.823153image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
34.74960002 2
 
< 0.1%
148.137883 1
 
< 0.1%
214.7840919 1
 
< 0.1%
201.7206695 1
 
< 0.1%
213.3839331 1
 
< 0.1%
214.1887838 1
 
< 0.1%
213.7126215 1
 
< 0.1%
200.1895938 1
 
< 0.1%
199.2768223 1
 
< 0.1%
200.0955782 1
 
< 0.1%
Other values (99988) 99988
> 99.9%
ValueCountFrequency (%)
0.005527827924 1
< 0.1%
0.01095869374 1
< 0.1%
0.01168374605 1
< 0.1%
0.01333666183 1
< 0.1%
0.0229663342 1
< 0.1%
0.02425788497 1
< 0.1%
0.02461910532 1
< 0.1%
0.02571591573 1
< 0.1%
0.02720599703 1
< 0.1%
0.02893798287 1
< 0.1%
ValueCountFrequency (%)
359.9998098 1
< 0.1%
359.9996152 1
< 0.1%
359.9990313 1
< 0.1%
359.9989651 1
< 0.1%
359.9970063 1
< 0.1%
359.9941245 1
< 0.1%
359.9936716 1
< 0.1%
359.9935681 1
< 0.1%
359.9893865 1
< 0.1%
359.9863626 1
< 0.1%

delta
Real number (ℝ)

Distinct99998
Distinct (%)> 99.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean24.135552
Minimum-18.785328
Maximum83.000519
Zeros0
Zeros (%)0.0%
Negative12060
Negative (%)12.1%
Memory size1.5 MiB
2024-10-04T10:15:47.080449image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-18.785328
5-th percentile-2.3657
Q15.1474766
median23.646462
Q339.901582
95-th percentile56.701131
Maximum83.000519
Range101.78585
Interquartile range (IQR)34.754106

Descriptive statistics

Standard deviation19.644608
Coefficient of variation (CV)0.81392824
Kurtosis-1.0430537
Mean24.135552
Median Absolute Deviation (MAD)17.26748
Skewness0.17506407
Sum2413531.1
Variance385.91061
MonotonicityNot monotonic
2024-10-04T10:15:47.349228image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
-0.6019312345 2
 
< 0.1%
0.9841090502 1
 
< 0.1%
51.01346105 1
 
< 0.1%
52.55626723 1
 
< 0.1%
51.46909077 1
 
< 0.1%
49.85246394 1
 
< 0.1%
51.26954441 1
 
< 0.1%
52.42180285 1
 
< 0.1%
52.59318628 1
 
< 0.1%
52.50418513 1
 
< 0.1%
Other values (99988) 99988
> 99.9%
ValueCountFrequency (%)
-18.78532808 1
< 0.1%
-17.63619832 1
< 0.1%
-17.61305644 1
< 0.1%
-17.57382002 1
< 0.1%
-17.46539063 1
< 0.1%
-17.45139007 1
< 0.1%
-17.4339462 1
< 0.1%
-17.36304673 1
< 0.1%
-17.28479137 1
< 0.1%
-17.22626675 1
< 0.1%
ValueCountFrequency (%)
83.00051859 1
< 0.1%
82.94762183 1
< 0.1%
82.81603025 1
< 0.1%
82.76442096 1
< 0.1%
82.75715318 1
< 0.1%
82.65631855 1
< 0.1%
82.56750029 1
< 0.1%
82.28865698 1
< 0.1%
79.34307616 1
< 0.1%
79.28929904 1
< 0.1%

u
Real number (ℝ)

Distinct93747
Distinct (%)93.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean22.080679
Minimum10.99623
Maximum32.78139
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 MiB
2024-10-04T10:15:47.597261image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum10.99623
5-th percentile18.43111
Q120.35241
median22.17914
Q323.68748
95-th percentile25.785051
Maximum32.78139
Range21.78516
Interquartile range (IQR)3.33507

Descriptive statistics

Standard deviation2.2510684
Coefficient of variation (CV)0.10194743
Kurtosis-0.53903957
Mean22.080679
Median Absolute Deviation (MAD)1.66685
Skewness-0.070298151
Sum2208045.8
Variance5.0673091
MonotonicityNot monotonic
2024-10-04T10:15:47.830591image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.63465 77
 
0.1%
24.63466 64
 
0.1%
24.63467 44
 
< 0.1%
24.63464 23
 
< 0.1%
24.63468 20
 
< 0.1%
24.63463 5
 
< 0.1%
21.68806 4
 
< 0.1%
24.63462 4
 
< 0.1%
24.63469 4
 
< 0.1%
19.95185 4
 
< 0.1%
Other values (93737) 99750
99.8%
ValueCountFrequency (%)
10.99623 1
< 0.1%
12.10168 1
< 0.1%
12.2624 1
< 0.1%
12.30349 1
< 0.1%
12.99664 1
< 0.1%
13.89799 1
< 0.1%
13.94716 1
< 0.1%
14.14713 1
< 0.1%
14.15199 1
< 0.1%
14.26381 1
< 0.1%
ValueCountFrequency (%)
32.78139 1
< 0.1%
30.66039 1
< 0.1%
29.32565 1
< 0.1%
29.23438 1
< 0.1%
29.19901 1
< 0.1%
29.18637 1
< 0.1%
29.04068 1
< 0.1%
28.90174 1
< 0.1%
28.79676 1
< 0.1%
28.77812 1
< 0.1%

g
Real number (ℝ)

Distinct92650
Distinct (%)92.7%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean20.631583
Minimum10.4982
Maximum31.60224
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 MiB
2024-10-04T10:15:48.079594image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum10.4982
5-th percentile17.072964
Q118.96524
median21.09993
Q322.123775
95-th percentile23.408264
Maximum31.60224
Range21.10404
Interquartile range (IQR)3.158535

Descriptive statistics

Standard deviation2.0373841
Coefficient of variation (CV)0.098750738
Kurtosis-0.37072148
Mean20.631583
Median Absolute Deviation (MAD)1.33242
Skewness-0.42803726
Sum2063137.7
Variance4.1509338
MonotonicityNot monotonic
2024-10-04T10:15:48.327489image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
25.11439 9
 
< 0.1%
25.11438 9
 
< 0.1%
25.11437 8
 
< 0.1%
21.65138 4
 
< 0.1%
21.94795 4
 
< 0.1%
21.80667 4
 
< 0.1%
21.76406 4
 
< 0.1%
22.41741 4
 
< 0.1%
22.03644 4
 
< 0.1%
22.19291 4
 
< 0.1%
Other values (92640) 99945
99.9%
ValueCountFrequency (%)
10.4982 1
< 0.1%
10.51139 1
< 0.1%
10.6718 1
< 0.1%
10.73097 1
< 0.1%
11.33897 1
< 0.1%
11.39234 1
< 0.1%
11.47435 1
< 0.1%
11.74518 1
< 0.1%
11.79892 1
< 0.1%
12.03599 1
< 0.1%
ValueCountFrequency (%)
31.60224 1
< 0.1%
30.607 1
< 0.1%
29.86258 1
< 0.1%
28.9032 1
< 0.1%
28.2066 1
< 0.1%
27.89482 1
< 0.1%
27.53211 1
< 0.1%
27.41465 1
< 0.1%
27.38851 1
< 0.1%
27.34772 1
< 0.1%

r
Real number (ℝ)

Distinct91900
Distinct (%)91.9%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.645777
Minimum9.82207
Maximum29.57186
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 MiB
2024-10-04T10:15:48.580578image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum9.82207
5-th percentile16.393042
Q118.135795
median20.12531
Q321.04479
95-th percentile22.070259
Maximum29.57186
Range19.74979
Interquartile range (IQR)2.908995

Descriptive statistics

Standard deviation1.8547631
Coefficient of variation (CV)0.094410268
Kurtosis-0.37613822
Mean19.645777
Median Absolute Deviation (MAD)1.24741
Skewness-0.5078796
Sum1964558
Variance3.440146
MonotonicityNot monotonic
2024-10-04T10:15:48.847136image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.80203 21
 
< 0.1%
24.80202 15
 
< 0.1%
24.80204 7
 
< 0.1%
20.72245 6
 
< 0.1%
20.76527 5
 
< 0.1%
20.74657 5
 
< 0.1%
20.5444 4
 
< 0.1%
20.78255 4
 
< 0.1%
20.6552 4
 
< 0.1%
20.24885 4
 
< 0.1%
Other values (91890) 99924
99.9%
ValueCountFrequency (%)
9.82207 1
< 0.1%
10.06854 1
< 0.1%
10.11604 1
< 0.1%
10.1946 1
< 0.1%
10.80343 1
< 0.1%
10.86379 1
< 0.1%
10.98255 1
< 0.1%
11.09069 1
< 0.1%
11.35229 1
< 0.1%
11.64166 1
< 0.1%
ValueCountFrequency (%)
29.57186 1
< 0.1%
29.37411 1
< 0.1%
27.62688 1
< 0.1%
27.59332 1
< 0.1%
27.39709 1
< 0.1%
27.33476 1
< 0.1%
27.30005 1
< 0.1%
27.07122 1
< 0.1%
27.06348 1
< 0.1%
26.79265 1
< 0.1%

i
Real number (ℝ)

Distinct92018
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean19.084865
Minimum9.469903
Maximum32.14147
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 MiB
2024-10-04T10:15:49.135530image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum9.469903
5-th percentile16.043817
Q117.73228
median19.40515
Q320.39651
95-th percentile21.607625
Maximum32.14147
Range22.671567
Interquartile range (IQR)2.66423

Descriptive statistics

Standard deviation1.7579003
Coefficient of variation (CV)0.092109656
Kurtosis-0.23484324
Mean19.084865
Median Absolute Deviation (MAD)1.21872
Skewness-0.40418294
Sum1908467.4
Variance3.0902136
MonotonicityNot monotonic
2024-10-04T10:15:49.403559image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
24.3618 6
 
< 0.1%
24.36181 6
 
< 0.1%
18.63308 5
 
< 0.1%
19.70201 4
 
< 0.1%
19.62323 4
 
< 0.1%
20.35125 4
 
< 0.1%
19.79566 4
 
< 0.1%
19.73572 4
 
< 0.1%
20.19353 4
 
< 0.1%
20.46932 4
 
< 0.1%
Other values (92008) 99954
> 99.9%
ValueCountFrequency (%)
9.469903 1
< 0.1%
10.00865 1
< 0.1%
10.05509 1
< 0.1%
10.56647 1
< 0.1%
10.87374 1
< 0.1%
10.95665 1
< 0.1%
11.26394 1
< 0.1%
11.29956 1
< 0.1%
11.31937 1
< 0.1%
11.51527 1
< 0.1%
ValueCountFrequency (%)
32.14147 1
< 0.1%
30.25009 1
< 0.1%
30.16359 1
< 0.1%
30.1546 1
< 0.1%
29.88921 1
< 0.1%
29.85405 1
< 0.1%
27.5034 1
< 0.1%
27.18834 1
< 0.1%
26.89399 1
< 0.1%
26.30939 1
< 0.1%

z
Real number (ℝ)

Distinct92006
Distinct (%)92.0%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean18.768988
Minimum9.612333
Maximum29.38374
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 MiB
2024-10-04T10:15:49.664018image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum9.612333
5-th percentile15.778304
Q117.46083
median19.0046
Q319.92112
95-th percentile21.462773
Maximum29.38374
Range19.771407
Interquartile range (IQR)2.46029

Descriptive statistics

Standard deviation1.7659819
Coefficient of variation (CV)0.094090415
Kurtosis-0.21000299
Mean18.768988
Median Absolute Deviation (MAD)1.17159
Skewness-0.25682184
Sum1876880
Variance3.118692
MonotonicityNot monotonic
2024-10-04T10:15:50.280698image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
22.8269 58
 
0.1%
22.82691 25
 
< 0.1%
22.82689 25
 
< 0.1%
22.82692 12
 
< 0.1%
19.8066 4
 
< 0.1%
19.65385 4
 
< 0.1%
19.54947 4
 
< 0.1%
19.50648 4
 
< 0.1%
19.9115 4
 
< 0.1%
18.89468 4
 
< 0.1%
Other values (91996) 99855
99.9%
ValueCountFrequency (%)
9.612333 1
< 0.1%
10.22551 1
< 0.1%
10.44131 1
< 0.1%
10.65056 1
< 0.1%
10.77889 1
< 0.1%
10.89738 1
< 0.1%
10.91847 1
< 0.1%
11.19448 1
< 0.1%
11.30247 1
< 0.1%
11.41484 1
< 0.1%
ValueCountFrequency (%)
29.38374 1
< 0.1%
28.79055 1
< 0.1%
28.23829 1
< 0.1%
27.80519 1
< 0.1%
27.67336 1
< 0.1%
26.59268 1
< 0.1%
26.42779 1
< 0.1%
26.2969 1
< 0.1%
26.13011 1
< 0.1%
26.0935 1
< 0.1%

redshift
Real number (ℝ)

Distinct99294
Distinct (%)99.3%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean0.57666657
Minimum-0.009970667
Maximum7.011245
Zeros412
Zeros (%)0.4%
Negative13724
Negative (%)13.7%
Memory size1.5 MiB
2024-10-04T10:15:50.547405image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum-0.009970667
5-th percentile-0.00032606178
Q10.054521695
median0.4241756
Q30.70417205
95-th percentile2.1877356
Maximum7.011245
Range7.0212157
Interquartile range (IQR)0.64965035

Descriptive statistics

Standard deviation0.73070865
Coefficient of variation (CV)1.267125
Kurtosis9.9728638
Mean0.57666657
Median Absolute Deviation (MAD)0.34490863
Skewness2.5235985
Sum57666.08
Variance0.53393514
MonotonicityNot monotonic
2024-10-04T10:15:50.803627image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
0 412
 
0.4%
7.011245 6
 
< 0.1%
0.004153254 4
 
< 0.1%
-0.004136076 3
 
< 0.1%
0.004153253 3
 
< 0.1%
0.6291372 3
 
< 0.1%
0.5471081 2
 
< 0.1%
1.272941 2
 
< 0.1%
0.1302064 2
 
< 0.1%
0.1761182 2
 
< 0.1%
Other values (99284) 99560
99.6%
ValueCountFrequency (%)
-0.009970667 1
 
< 0.1%
-0.007351653 1
 
< 0.1%
-0.006863183 1
 
< 0.1%
-0.006055369 1
 
< 0.1%
-0.005675106 1
 
< 0.1%
-0.004712832 1
 
< 0.1%
-0.004254519 1
 
< 0.1%
-0.004136078 1
 
< 0.1%
-0.004136076 3
< 0.1%
-0.004020985 1
 
< 0.1%
ValueCountFrequency (%)
7.011245 6
< 0.1%
7.011103 1
 
< 0.1%
7.010295 1
 
< 0.1%
7.010272 1
 
< 0.1%
7.010263 1
 
< 0.1%
7.009989 1
 
< 0.1%
7.0094 1
 
< 0.1%
7.008322 1
 
< 0.1%
7.007396 1
 
< 0.1%
7.00387 2
 
< 0.1%

MJD
Real number (ℝ)

Distinct2180
Distinct (%)2.2%
Missing0
Missing (%)0.0%
Infinite0
Infinite (%)0.0%
Mean55588.654
Minimum51608
Maximum58932
Zeros0
Zeros (%)0.0%
Negative0
Negative (%)0.0%
Memory size1.5 MiB
2024-10-04T10:15:51.047379image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Quantile statistics

Minimum51608
5-th percentile52336.9
Q154234
median55869
Q356777
95-th percentile58201
Maximum58932
Range7324
Interquartile range (IQR)2543

Descriptive statistics

Standard deviation1808.4922
Coefficient of variation (CV)0.032533478
Kurtosis-0.7731643
Mean55588.654
Median Absolute Deviation (MAD)1257
Skewness-0.3818618
Sum5.5588098 × 109
Variance3270644.1
MonotonicityIncreasing
2024-10-04T10:15:51.347394image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram with fixed size bins (bins=50)
ValueCountFrequency (%)
56625 249
 
0.2%
58162 228
 
0.2%
56658 217
 
0.2%
56390 216
 
0.2%
56385 201
 
0.2%
57574 200
 
0.2%
58428 193
 
0.2%
56074 190
 
0.2%
56722 188
 
0.2%
55863 186
 
0.2%
Other values (2170) 97931
97.9%
ValueCountFrequency (%)
51608 12
< 0.1%
51609 7
< 0.1%
51613 4
 
< 0.1%
51615 4
 
< 0.1%
51630 14
< 0.1%
51633 1
 
< 0.1%
51637 6
< 0.1%
51658 2
 
< 0.1%
51662 7
< 0.1%
51663 11
< 0.1%
ValueCountFrequency (%)
58932 61
0.1%
58931 8
 
< 0.1%
58930 31
< 0.1%
58928 39
< 0.1%
58895 2
 
< 0.1%
58543 36
< 0.1%
58526 36
< 0.1%
58523 36
< 0.1%
58522 40
< 0.1%
58515 39
< 0.1%

class
Categorical

Distinct3
Distinct (%)< 0.1%
Missing0
Missing (%)0.0%
Memory size1.5 MiB
GALAXY
59445 
STAR
21593 
QSO
18961 

Length

Max length6
Median length6
Mean length4.9993
Min length3

Characters and Unicode

Total characters499925
Distinct characters10
Distinct categories1 ?
Distinct scripts1 ?
Distinct blocks1 ?
The Unicode Standard assigns character properties to each code point, which can be used to analyse textual variables.

Unique

Unique0 ?
Unique (%)0.0%

Sample

1st rowGALAXY
2nd rowGALAXY
3rd rowGALAXY
4th rowQSO
5th rowGALAXY

Common Values

ValueCountFrequency (%)
GALAXY 59445
59.4%
STAR 21593
 
21.6%
QSO 18961
 
19.0%

Length

2024-10-04T10:15:51.597543image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Histogram of lengths of the category

Common Values (Plot)

2024-10-04T10:15:51.780788image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
ValueCountFrequency (%)
galaxy 59445
59.4%
star 21593
 
21.6%
qso 18961
 
19.0%

Most occurring characters

ValueCountFrequency (%)
A 140483
28.1%
G 59445
11.9%
L 59445
11.9%
X 59445
11.9%
Y 59445
11.9%
S 40554
 
8.1%
T 21593
 
4.3%
R 21593
 
4.3%
Q 18961
 
3.8%
O 18961
 
3.8%

Most occurring categories

ValueCountFrequency (%)
Uppercase Letter 499925
100.0%

Most frequent character per category

Uppercase Letter
ValueCountFrequency (%)
A 140483
28.1%
G 59445
11.9%
L 59445
11.9%
X 59445
11.9%
Y 59445
11.9%
S 40554
 
8.1%
T 21593
 
4.3%
R 21593
 
4.3%
Q 18961
 
3.8%
O 18961
 
3.8%

Most occurring scripts

ValueCountFrequency (%)
Latin 499925
100.0%

Most frequent character per script

Latin
ValueCountFrequency (%)
A 140483
28.1%
G 59445
11.9%
L 59445
11.9%
X 59445
11.9%
Y 59445
11.9%
S 40554
 
8.1%
T 21593
 
4.3%
R 21593
 
4.3%
Q 18961
 
3.8%
O 18961
 
3.8%

Most occurring blocks

ValueCountFrequency (%)
ASCII 499925
100.0%

Most frequent character per block

ASCII
ValueCountFrequency (%)
A 140483
28.1%
G 59445
11.9%
L 59445
11.9%
X 59445
11.9%
Y 59445
11.9%
S 40554
 
8.1%
T 21593
 
4.3%
R 21593
 
4.3%
Q 18961
 
3.8%
O 18961
 
3.8%

Interactions

2024-10-04T10:15:43.847590image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:27.049088image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:28.847761image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:30.497629image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:34.122445image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:36.014559image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:37.896996image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:39.615692image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:42.050075image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:44.050274image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:27.283175image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:29.033598image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:30.775293image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:34.332764image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:36.233249image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:38.121573image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:39.915886image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:42.268619image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:44.233462image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:27.483853image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:29.196759image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:30.996582image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:34.530649image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:36.425529image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:38.313689image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:40.116586image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:42.450039image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:44.424319image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:27.663197image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:29.365915image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:31.189812image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:34.720575image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:36.614390image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:38.500103image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:40.363697image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:42.632490image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:44.614650image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:27.854003image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:29.533480image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:31.368416image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:34.926047image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:36.819161image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:38.650363image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:40.630522image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:42.799566image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:44.814833image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:28.056802image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:29.733083image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:33.274451image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:35.204088image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:37.048905image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:38.849916image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:40.937362image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:43.016273image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:44.984490image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:28.233176image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:29.900255image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:33.448042image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:35.390146image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:37.251751image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:39.019924image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:41.397296image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:43.219540image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:45.202296image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:28.448553image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:30.097048image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:33.667140image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:35.601413image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:37.463742image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:39.231754image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:41.616666image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:43.433747image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:45.399912image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:28.632944image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:30.283447image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:33.880384image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:35.798953image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:37.666804image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:39.417624image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:41.815424image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
2024-10-04T10:15:43.651128image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/

Missing values

2024-10-04T10:15:45.653226image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
A simple visualization of nullity by column.
2024-10-04T10:15:45.997213image/svg+xmlMatplotlib v3.9.1, https://matplotlib.org/
Nullity matrix is a data-dense display which lets you quickly visually pick out patterns in data completion.

Sample

alphadeltaugrizredshiftMJDclass
df_index
5390148.1378830.98410917.9404815.8507614.9241314.4868414.151160.04676451608GALAXY
12866147.3668400.96837520.5774318.6006717.7956017.3457617.054820.10233751608GALAXY
25727148.753530-0.59616822.9062721.3522019.5397418.7014318.190420.46898751608GALAXY
25846148.428864-0.86328318.9368919.0768718.7311418.6987718.707231.30131451608QSO
37304147.165549-0.89131321.2110118.9208517.6524517.1453016.756570.16742351608GALAXY
41782147.082750-1.21564722.8916719.8391018.3507817.7253317.378080.00011951608STAR
60850149.0323920.28814319.6900118.4588817.7500017.3339717.078450.12699151608GALAXY
62175149.1849010.24210719.9649318.1850817.2795816.8763416.573290.08680151608GALAXY
64380147.9053710.41210919.6471418.2840617.6248217.2254916.915000.09351351608GALAXY
70556148.4011621.01270520.1278018.4078617.5917017.1646416.885500.09845951608GALAXY
alphadeltaugrizredshiftMJDclass
df_index
75109131.0034990.95978821.9117821.2573320.9912320.7066220.234650.74909258932QSO
76131131.1652450.98690423.8359923.2677821.4853620.7193120.223990.67047858932GALAXY
76466131.2192360.97016824.3681022.3493321.0559420.5378620.256710.50863858932GALAXY
81625131.056936-1.46882920.3292920.1170620.1331420.1700820.182960.00415358932STAR
82395130.707355-1.53237019.6012117.9026717.2663417.0336416.892090.00035758932STAR
82606130.690218-1.70505921.6415421.1659120.5532620.4171219.900970.36685858932QSO
82607130.919840-1.38724920.2514520.2294320.0976420.1255620.022441.33799458932QSO
89144130.701162-1.60443920.5149420.5729120.1806520.1428120.129811.24026058932QSO
89434130.5953421.66166524.1547822.2675620.6847619.9281819.559380.41759458932GALAXY
92417131.0126430.91907222.8891424.0237722.8078421.6149121.199570.74926458932GALAXY